Top Senior Analysis Reporting Jobs in Cleveland, OH

Designs, builds, deploys, and maintains scalable data pipelines, data lake systems, batch and streaming processing, MLOps frameworks, data documentation tooling, and an agentic data exploration platform. The role supports customer-facing products and enables engineering teams through reliable infrastructure, observability, data discovery, and AI capabilities.

Own analytics for Root’s Customer Experience domain and policyholder retention. Develop metrics, analytical frameworks, experimentation systems, and strategic recommendations. Partner cross-functionally with Product, Engineering, Data Science, and Operations to shape roadmaps, evaluate customer initiatives, quantify business impact, and influence senior leadership decisions through rigorous analysis and clear communication.

Analyzes business and operational needs, gathers requirements, evaluates data and systems, and recommends technology solutions. Develops advanced SQL queries, reports, system models, and process improvements. Responsibilities include troubleshooting, data architecture integration, software and hardware solution design, database analysis, automation using scheduling or RPA tools, and project leadership. Senior levels guide other analysts and assess technology’s business impact.

Design and implement enterprise data architectures supporting batch and real-time analytics, ETL/ELT, data warehouses, streaming pipelines, CDC, and cloud data platforms. Build AI-ready data infrastructure for RAG, vector search, and Generative AI applications. The role requires production experience with Treasure Data/CDP, Kafka, Snowflake or Databricks, cloud services, and modern AI data engineering technologies.

Lead analytics partner to Community Support, driving data-driven roadmaps, scalable reporting and measurement, causal inference and experimentation, and improvements to agent/guest/host experiences via analytics, modeling, and stakeholder influence.

Delivers financial and operational reporting, dashboards, forecasting, variance analysis, and profitability insights for Financial Services clients. Uses SQL, Power BI, and Excel to validate data, identify anomalies, support client implementations, and improve reporting processes. Partners cross-functionally with accounting, operations, analytics, FP&A, vendors, and leadership while maintaining data governance, documentation, and reporting standards.

Build and maintain production data pipelines that transform robot logs and telemetry into reliable, queryable datasets. Design Spark-based ETL workflows, orchestrate processing with Airflow or similar tools, manage gold-layer datasets, and implement data quality, schema evolution, monitoring, and metadata practices. Collaborate with robotics, hardware, reliability, analytics, and ML teams on data modeling, fleet insights, debugging, and root-cause analysis. The role may also contribute to Python, Java, or C++ libraries supporting data capture and consumption.

Leads development and maintenance of actuarial data marts, datasets, extracts, reports, and analytical solutions supporting claims analysis, IBNR reserving, forecasting, trend analysis, and financial reporting. Partners with actuarial, finance, medical economics, and data teams to validate and reconcile healthcare data, automate refreshes, ensure auditability, and improve data quality. Provides technical leadership, requirements expertise, recommendations, training, and direction to junior staff and business partners.

Designs and leads production-grade batch, incremental, streaming, and real-time data pipelines across Microsoft Fabric and Azure. Builds Delta Lake medallion architectures, dimensional and Data Vault models, CDC and incremental-loading solutions, CI/CD automation, governance, security, observability, and data-quality controls. Supports migrations to Fabric, prepares governed data for AI and RAG workloads, and leads client-facing engineering workstreams, estimates, risk management, mentoring, and operational handover.

Analyze and maintain recruitment, onboarding, workforce, participant, and program-performance data for the NIH DataForce Service Program. Develop trackers, dashboards, reports, and briefing materials; monitor participant lifecycle activities; identify data-quality issues, risks, trends, and process improvements; and support recurring monthly and quarterly analyses. Collaborate with program managers, mentors, coordinators, and government stakeholders while protecting sensitive information and ensuring Section 508 accessibility compliance.